RNA Sequencing in Clinical Oncology for Metabolism and Immunity

246.9K

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351

authors

43

articles

RNA Sequencing in Clinical Oncology for Metabolism and Immunity

246.9K

views

351

authors

43

articles

Editors

4

Qingdao University, The Affiliated Qingdao Central Hospital of Qingdao University

The Affiliated Hospital of Qingdao University

Anton A. Buzdin

European Organisation for Research and Treatment of Cancer

University of California, Los Angeles

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Tumor cells exhibit an upregulation in glycolysis, glycogen metabolism, and gluconeogenesis as opposed to normal cells. The metabolic reprogramming underlying the Warburg effect and other changes in glucose metabolism are driven by several oncogenes and tumor suppressors. Immunotherapies based on cancer metabolism have been developed but have yet to show success in clinical trials. RNA sequencing (RNAseq) is one of the most commonly used techniques in life sciences, and has been widely used in cancer research. Driven by various biological and technical questions, the techniques of RNAseq have progressed rapidly from bulk RNAseq, laser-captured micro-dissected RNAseq, and single-cell RNAseq to digital spatial RNA profiling, spatial transcriptomics, and direct in situ sequencing.

RNA sequencing in clinical oncology includes bulk RNA-seq, single cell RNA-seq and spatial RNA-seq.We anticipate that bulk RNAseq, among the three, will remain the primary choice for clinical oncology in the near future. The application of single cell sequencing will be expanded when it becomes more cost-effective, and the technologies with spatial content will be the final destiny in precision oncology.

In this Research Topic, we aim to discuss the application of RNA sequencing in clinical oncology for metabolism and immunity. We welcome submissions of Original Research papers and Reviews focusing on but not limited to:
- RNA-Seq based applications for cancer diagnostics and theranostics in metabolism and immunity
- Genome-wide approaches for clinical oncology in metabolism and immunity
- High throughput RNA/Transcriptome approaches in cancer molecular diagnostics
- RNA-Seq for predicting response to targeted therapeutics and chemotherapy regimens
- RNA-Seq for predicting response to immunotherapeutics
- RNA-Seq for predicting response to radiation therapy

Tumor cells exhibit an upregulation in glycolysis, glycogen metabolism, and gluconeogenesis as opposed to normal cells. The metabolic reprogramming underlying the Warburg effect and other changes in glucose metabolism are driven by several oncogenes and tumor suppressors. Immunotherapies based on cancer metabolism have been developed but have yet to show success in clinical trials. RNA sequencing (RNAseq) is one of the most commonly used techniques in life sciences, and has been widely used in cancer research. Driven by various biological and technical questions, the techniques of RNAseq have progressed rapidly from bulk RNAseq, laser-captured micro-dissected RNAseq, and single-cell RNAseq to digital spatial RNA profiling, spatial transcriptomics, and direct in situ sequencing.

RNA sequencing in clinical oncology includes bulk RNA-seq, single cell RNA-seq and spatial RNA-seq.We anticipate that bulk RNAseq, among the three, will remain the primary choice for clinical oncology in the near future. The application of single cell sequencing will be expanded when it becomes more cost-effective, and the technologies with spatial content will be the final destiny in precision oncology.

In this Research Topic, we aim to discuss the application of RNA sequencing in clinical oncology for metabolism and immunity. We welcome submissions of Original Research papers and Reviews focusing on but not limited to:
- RNA-Seq based applications for cancer diagnostics and theranostics in metabolism and immunity
- Genome-wide approaches for clinical oncology in metabolism and immunity
- High throughput RNA/Transcriptome approaches in cancer molecular diagnostics
- RNA-Seq for predicting response to targeted therapeutics and chemotherapy regimens
- RNA-Seq for predicting response to immunotherapeutics
- RNA-Seq for predicting response to radiation therapy

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Editors

Qingdao University, The Affiliated Qingdao Central Hospital of Qingdao University

The Affiliated Hospital of Qingdao University

Anton A. Buzdin

European Organisation for Research and Treatment of Cancer

University of California, Los Angeles

Impact

246,887 Total views

155,224 Article views

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2,752 Topic views

Published In

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Frontiers in Oncology

Pharmacology of Anti-Cancer Drugs, Cancer Genetics

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Frontiers in Pharmacology

Pharmacology of Anti-Cancer Drugs

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Frontiers in Genetics

Cancer Genetics

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